Abbafati Cristiana, Nieddu Luciano, Cattani Giorgio, Reatini Maria Antonietta, Ponzani Paola
Department of Juridical and Economic Studies, Sapienza University of Rome, P.le Aldo Moro, 5, Rome, 00185, Italy.
Department of Humanistic and International Social Sciences, UNINT University for International Studies, Via C. Colombo, 200, Rome, 00147, Italy.
Sci Rep. 2025 Aug 3;15(1):28326. doi: 10.1038/s41598-025-13733-6.
A growing body of literature supports the association between ambient particulate pollution and the risk of type 2 diabetes (T2DM). Both issues are particularly relevant in Italy. This study investigates the relationship between T2DM and exposure to PM and PM in Italian municipalities from 2013 to 2021. Data on T2DM were provided by the Italian Association of Diabetologists (AMD), representing the only national outpatient dataset not based on self-reported information. Air pollution data, sourced from the Italian Institute for Environmental Protection and Research, ISPRA, were summarized using the population-weighted exposure (PWE) indicator. Both datasets were made available through a dedicated research agreement. Random effects models and non-parametric methods were applied to assess the association between air pollution and T2DM. Results indicate a statistically significant relationship, particularly between T2DM and PM2.5. T2DM incidence rates were significantly negatively associated with time (coefficient = - 0.07961, p < 0.01), indicating a decreasing trend over time. After adjusting for other covariates, PM population-weighted exposure was not significantly associated with incidence rates (coefficient = - 0.00057, p = 0.58). On the other hand, increases in the ratio of PM to PM (pwratio) were significantly positively associated with increases in T2DM incidence rates (coefficient = 0.52304, p < 0.01) at the municipal level. T2DM prevalence proportions were significantly positively associated with time (coefficient = 0.01749, p < 0.01), suggesting an increasing trend over time. PM was significantly negatively associated with prevalence proportions (coefficient = - 0.00298, p = 0.03), while increases in pwratio were significantly positively associated with increases in prevalence proportions (coefficient = 0.18724, p < 0.01). Thus, municipalities with a higher share of PM within the same level of PM, tended to show higher T2DM prevalence proportions and incidence rates, consistent with the spatial distribution of air pollution and disease burden observed across Italy.
越来越多的文献支持环境颗粒物污染与2型糖尿病（T2DM）风险之间的关联。这两个问题在意大利尤为相关。本研究调查了2013年至2021年意大利各城市中T2DM与接触细颗粒物（PM）和粗颗粒物（PM）之间的关系。T2DM数据由意大利糖尿病学家协会（AMD）提供，该协会代表了唯一一个并非基于自我报告信息的全国门诊数据集。空气污染数据来源于意大利环境保护与研究机构ISPRA，使用人口加权暴露（PWE）指标进行汇总。两个数据集均通过专门的研究协议提供。应用随机效应模型和非参数方法来评估空气污染与T2DM之间的关联。结果表明存在统计学上的显著关系，特别是在T2DM与PM2.5之间。T2DM发病率与时间呈显著负相关（系数 = -0.07961，p < 0.01），表明随着时间推移呈下降趋势。在调整其他协变量后，PM人口加权暴露与发病率无显著关联（系数 = -0.00057，p = 0.58）。另一方面，在城市层面，PM与PM的比值（pwratio）增加与T2DM发病率增加显著正相关（系数 = 0.52304，p < 0.01）。T2DM患病率与时间显著正相关（系数 = 0.01749，p < 0.01），表明随着时间推移呈上升趋势。PM与患病率显著负相关（系数 = -0.00298，p = 0.03），而pwratio增加与患病率增加显著正相关（系数 = 0.18724，p < 0.01）。因此，在相同PM水平下PM占比更高的城市，往往表现出更高的T2DM患病率和发病率，这与意大利观察到的空气污染和疾病负担的空间分布一致。
